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gradient | Examples See Also |
FX = gradient(F) [FX,FY] = gradient(F) [Fx,Fy,Fz,...] = gradient(F) [...] = gradient(F,h) [...] = gradient(F,h1,h2,...)The gradient of a function of two variables, F(x,y), is defined as:
FX = gradient(F)
where F
is a vector returns the one-dimensional numerical gradient of F
. FX
corresponds to , the differences in the x direction.
[FX,FY] = gradient(F)
where F
is a matrix returns the x and y components of the two-dimensional numerical gradient. FX
corresponds to , the differences in the x
(column) direction. FY
corresponds to , the differences in the y (row) direction. The spacing between points in each direction is assumed to be one.
[FX,FY,FZ,...] = gradient(F)
where F
has N dimensions
returns the N
components of the gradient of F
.
There are two ways to control the spacing between values in F
:
A single spacing value, h
, specifies the spacing between points in every direction.
N
spacing values (h1,h2,...
) specify the spacing for each dimension of F
. Scalar spacing parameters specify a constant spacing for each dimension. Vector parameters specify the coordinates of the values along corresponding dimensions of F
. In this case, the length of the vector must match the size of the corresponding dimension.
[...] = gradient(F,h)
where h
is a scalar uses h
as the spacing between points in each direction.
[...] = gradient(F,h1,h2,...)
with N
spacing parameters specifies the spacing for each dimension of F
.
The statements
v = -2:0.2:2; [x,y] = meshgrid(v); z = x .* exp(-x.^2 - y.^2); [px,py] = gradient(z,.2,.2); contour(v,v,z), hold on, quiver(px,py), hold offproduce
F(:,:,1) = magic(3); F(:,:,2) = pascal(3);gradient(F)
takesdx
=dy
=dz
=1
.[PX,PY,PZ] = gradient(F,0.2,0.1,0.2)
takesdx = 0.2
,dy = 0.1
, anddz = 0.2
.
del2
Discrete Laplacian
diff
Differences and approximate derivatives